Replication Materials for "The Conditional Effects of Microtargeted Facebook Advertisements on Voter Turnout" (Haenschen, 2022)

This folder contains the code and data acquisition process needed to replicate the analysis in the above-mentioned article. 

I. Data acquisition

Data for this study was provided by Catalist, a commercial voter file vendor. Because the data includes several of their proprietary modeling scores, and the data was provided to the researcher at no cost, Catalist is not willing to make the data available publicly on the Internet. 

Data can be obtained from the researcher. All requests that meet the criteria will be approved. To obtain the data, the requestor(s) must complete a data-sharing agreement with the IRB of their choosing and complete the form in the file ("DataSharingAgreement_Catalist-Haenschen").

Variables in the dataset consist of:

RowID (sequential to provide an ID for each participant)
Group (treatment condition)
county.match (did the person move between counties during the experiment)
dob.match (does the birthdate in the update match the birthdate in the original export)
CONGRESSIONAL_DISTRICT
VOTE_PROPENSITY_2018 (Probability of voting in 2018 Midterm)
PARTISANSHIP_SCORE (Democratic support score)
VOTER_STATUS
X2018_GENERAL_VOTE_HISTORY
X2016_GENERAL_VOTE_HISTORY
CountyName
Age
length.reg (Registration length in months)
Sex

All of the other variables will be created as part of the cleaning / coding. 

II. Analysis Code

This analysis was conducted in R using R Studio version 1.0.153 for Mac. 

To run the analysis, I suggest you proceed in the following order: 

1. FacebookAdsMainText

This file contains all of the code needed to clean and prepare the data for analysis, including removing movers and bad matches, and coding variables. 

It then includes all of the code to produce Table 3, minus the omnibus FDR adjustment (more on that later). It will also produce the point estimates used to create Figures 1 and 2. 

2. FacebookAdsSupplement

The first section of this file contains all of the code needed to prepare the analysis presented in the supplemental materials, from Table A1 through A12. 

It also contains the code to run a supplemental analysis that verifies that any departures from the pre-analysis plan in terms of subject exclusion (bad birthday matches). This code will produce the results reported in the columns labeled "Including Bad Birthdays" for tables A13-A20.  

3. FDR adjustment

This paper uses a False Discovery Rate (FDR) adjustment to address multiple comparisons. this performs the FDR adjustment across the five main models reported in the paper. Note that throughout the code, model-by-model FDR adjustments are also available; these tend to be more conservative in this instance. 